Run
10228360

Run 10228360

Task 2077 (Supervised Classification) baseball Uploaded 04-06-2019 by Peter Fontana
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Flow

sklearn.pipeline.Pipeline(Imputer=sklearn.impute.SimpleImputer,OneHotEncode r=sklearn.preprocessing._encoders.OneHotEncoder,fs=sklearn.feature_selectio n.univariate_selection.SelectPercentile,rf=sklearn.ensemble.forest.RandomFo restClassifier)(1)Automatically created scikit-learn flow.
sklearn.impute.SimpleImputer(10)_copytrue
sklearn.impute.SimpleImputer(10)_fill_valuenull
sklearn.impute.SimpleImputer(10)_missing_valuesNaN
sklearn.impute.SimpleImputer(10)_strategy"constant"
sklearn.impute.SimpleImputer(10)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(51)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(51)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(51)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(51)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(51)_max_features"auto"
sklearn.ensemble.forest.RandomForestClassifier(51)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(51)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(51)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(51)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(51)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(51)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(51)_n_estimators10
sklearn.ensemble.forest.RandomForestClassifier(51)_n_jobsnull
sklearn.ensemble.forest.RandomForestClassifier(51)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(51)_random_state37197
sklearn.ensemble.forest.RandomForestClassifier(51)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(51)_warm_startfalse
sklearn.preprocessing._encoders.OneHotEncoder(9)_categorical_featuresnull
sklearn.preprocessing._encoders.OneHotEncoder(9)_categoriesnull
sklearn.preprocessing._encoders.OneHotEncoder(9)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(9)_handle_unknown"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(9)_n_valuesnull
sklearn.preprocessing._encoders.OneHotEncoder(9)_sparsefalse
sklearn.pipeline.Pipeline(Imputer=sklearn.impute.SimpleImputer,OneHotEncoder=sklearn.preprocessing._encoders.OneHotEncoder,fs=sklearn.feature_selection.univariate_selection.SelectPercentile,rf=sklearn.ensemble.forest.RandomForestClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(Imputer=sklearn.impute.SimpleImputer,OneHotEncoder=sklearn.preprocessing._encoders.OneHotEncoder,fs=sklearn.feature_selection.univariate_selection.SelectPercentile,rf=sklearn.ensemble.forest.RandomForestClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "OneHotEncoder", "step_name": "OneHotEncoder"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "fs", "step_name": "fs"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "rf", "step_name": "rf"}}]
sklearn.feature_selection.univariate_selection.SelectPercentile(3)_percentile10
sklearn.feature_selection.univariate_selection.SelectPercentile(3)_score_func{"oml-python:serialized_object": "function", "value": "sklearn.feature_selection.univariate_selection.f_classif"}

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

15 Evaluation measures

Area under ROC curve
0.6961 ± 0.0727
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.0294 ± 0.0612
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.1978 ± 0.0852
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0682 ± 0.0041
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1164 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Number of instances
1340
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9082 ± 0.0061
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.5401 ± 0.0169
Cross-validation details (10-fold Crossvalidation)
Recall
0.9082 ± 0.0061
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.586 ± 0.034
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2405 ± 0.0047
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2361 ± 0.0103
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9818 ± 0.043
Cross-validation details (10-fold Crossvalidation)